Quality indicator survey of clinical practice guidelines for esophagogastric junction cancer 2023
Bibliographic record
Abstract
Clinical practice guidelines for esophagogastric junction cancer (EGJ GLs) were published in 2023. In order to evaluate how EGJ GLs have been adopted into clinical practice worldwide and to identify any outstanding clinical questions to be addressed in the next edition, this survey was conducted. An electronic questionnaire was developed. The questionnaire comprised 16 questions designed to assess the adoption of the guideline. Responses were collected online. The survey was conducted by the EGJ working group of International Gastric Cancer Association (IGCA) following approval from the guideline committee of The International Society for Diseases of the Esophagus (ISDE). As results, we received 344 valid and complete responses. 55% of respondents were from East Asia followed by Europe, Central/South America, and Central/West Asia. 80% of respondents recognized and followed the guidelines to some extent. There was still diversity in the extent of lymphadenectomy for EGJ cancers with an esophageal invasion of 2-4 cm. Although white light imaging (WLE) alone was recommended in the EGJ GLs, both WLE and image enhanced endoscopy were used in 86% of respondents. The perioperative treatment was shown to be highly diverse worldwide. While 50% of respondents provided perioperative chemotherapy, preoperative chemotherapy without adjuvant treatment and upfront surgery were still the first treatment option in 15% of respondents. In conclusion, the current survey conducted by IGCA and ISDE identified the current standard and remaining issues of EGJ cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".